System and method for determining antenna probabilities in sub-areas of a geographical area

ABSTRACT

Methods and systems are provided for determining signal source probabilities. Signal source probabilities, for a plurality of sub-areas of a geographic area covered by a plurality of signal sources, may be determined. For each one of the plurality of sub-areas, the signal source probabilities may be determined based on probable field strengths of the plurality of signal sources for the one of the plurality of sub-areas, and the signal source probabilities for that one of the plurality of sub-areas indicate the probability that a mobile device, located in that one of the plurality of sub-areas, is operable to detect a particular signal source for communicating. Determining signal source probabilities may comprise calculating expected field strengths in the plurality of sub-areas. Determining signal source probabilities may comprise obtaining power information indicating a detected power of respective signals received by the mobile device from multiple transmitters.

FIELD OF THE INVENTION

The present invention relates to a system and a method for locating amobile communication terminal in a geographical area. Specifically, thepresent invention relates to a computer system and acomputer-implemented method for locating a mobile communication terminalassociated with a mobile radio network covering the geographical area.

BACKGROUND OF THE INVENTION

For various location based services as well as for handling emergencysituations, it is essential to determine as accurately as possible thegeographical location of a user of a mobile communication terminal.Mobile communication terminals include, for example, mobile radio(cellular) telephones or personal digital assistants (PDA) as well asother portable computers with communication modules for mobile radionetworks, such as GSM (Global System for Mobile Communication) or UMTS(Universal Mobile Telecommunication System). Although there are mobilecommunication terminals available which include a GPS-receiver (GlobalPositioning System) or another satellite-based positioning system, thereis still a need for other location methods, as for example locatingmobile communication terminals which are not equipped with suchpositioning systems, mobile communication terminals which have their GPSturned off or inside of buildings where the GPS signal is too weak. Itis known from the mobile network which antenna the user is using.However, particularly in rural areas, an area served by an antenna cancover a very large geographical area. Unfortunately today calculationsof these areas are not accurate, often they are too large or they arenot reliable, and in reality mobile communication terminals are oftenlocated outside of these areas (low hit rate).

GB 2352134 describes a method of locating a mobile telephone based on acalculation of expected signal properties such as signal strength orobserved time differences for a plurality of possible locations, e.g.arranged in a grid. The expected signal property is compared to ameasured signal property. Based on the comparison, determined is theprobability that the mobile telephone is at one or more of thelocations. Thus, the method of GB 2352134 is based on the actual valuesof the field strength or time differences measured at the mobiletelephone. However, these values would have to be transmitted from themobile telephones to a centralized measuring system and are thereforenot necessarily available for locating a mobile telephone. Furthermore,manufacturers of proprietary network components do not necessarily makesuch values available to the operators of mobile networks or they sellthem at considerable cost. The method does also fail when there are lessthan 3 antennas available, or if the visible antennas are arranged alonga line, for example, in mountain areas.

SUMMARY OF THE INVENTION

It is an object of this invention to provide a system and a method forlocating a mobile communication terminal in a geographical area, whichsystem and method do not have some of the disadvantages of the priorart. In particular, it is an object of this invention to provide asystem and a method for locating a mobile communication terminal in ageographical area with accuracy beyond cell level, but without the needfor measuring at the mobile communication terminal signal propertiessuch as signal strength or observed time differences. In particular, itis a further object of this invention to provide a system and a methodfor locating a mobile communication terminal in a geographical areawhere there is only coverage of one or two antennas or where thecoverage is only provided by antennas arranged along a line.

According to the present invention, these objects are achievedparticularly through the features of the independent claims. Inaddition, further advantageous embodiments follow from the dependentclaims and the description.

According to the present invention, the above-mentioned objects areparticularly achieved in that, for locating a mobile communicationterminal associated with a mobile radio network covering a geographicalarea, the geographical area is divided into a plurality of sub-areas.For example, the geographical area is divided into sub-areas of equalshape and size, having a diameter in the range of 50 to 150 meters. Forexample, the sub-areas are squares arranged in a grid, or hexagonsarranged in a comb structure. Based on field strengths expected in thesub-areas for antennas located in the geographical area, antennaprobabilities are determined for the sub-areas. The antennaprobabilities indicate for at least some of the antennas, theprobability that the mobile communication terminal, when located in aparticular sub-area, uses the respective antenna. For example, for asub-area, the antenna probabilities are determined for a limited numberof antennas that have the strongest field strengths expected in therespective sub-area, e.g. for each sub-area, the antenna probabilitiesare determined for the 7 or 14 antennas having the strongest expectedfield strength in the sub-area. Determined is the antenna used by themobile communication terminal, e.g. the current antenna (for determiningthe current location) or the antenna used (for determining the currentor last known location) from identification data provided by the mobileradio network, such as cell or base station identification data, or anantenna associated with the user or the mobile communication terminal,respectively, by an operator, for example (e.g. for determining ahistorical or hypothetical location). Subsequently, for the sub-areaslocation probabilities are determined based on the antenna probabilitiesassociated with the antenna used, each location probability indicatingthe probability that the mobile communication terminal is located in therespective sub-area. Determining and storing for the antennasprobabilities that indicate the likelihood that the mobile communicationterminal, when located in a particular sub-area, uses the respectiveantenna, makes it possible to locate the mobile communication terminalin the geographical area based on the antenna used, whereby thedetermined location area of the mobile user is much smaller than thearea each antenna covers physically, but without the need for measuringat the mobile communication terminal signal properties such as signalstrength or observed time differences, and without the requirement tohave everywhere coverage of at least three antennas not arranged along aline.

In a preferred embodiment, the antenna probabilities for the sub-areasare determined based on normal distributions of the field strengthsexpected in the sub-areas from the antennas. Using normal distributionsof the expected and/or simulated field strengths takes intoconsideration that the real field strength varies within a sub-areadepending on a variety of factors such as the actual position within thesub-area, the current weather conditions, the type of communicationterminal used, and how the communication terminal is held by the user,i.e. oriented in space.

In a further embodiment, different standard deviations are used for thedistributions of the expected field strengths, higher values of thestandard deviation being used with increasing distance between antennaand sub-area. Thus, it is possible to take into consideration higherdeviations of the field strength for locations more remote from theantenna. It is also possible to consider different deviations of fieldstrength distribution, depending on the type of mobile radio networktechnology, e.g. different deviations for a GSM or UMTS-network.

In a further embodiment, the antenna probabilities are refined usingdistributions of the distance between the mobile communication terminaland an antenna, the distributions being estimated in advance based onparameters provided by the mobile radio network. Specifically, largeareas with at least a minimum antenna probability are reduced in size,if the network does not only deliver the antenna which was used by themobile terminal of the user, but also parameters which indicate thedistance between the mobile terminal and its antenna, as for example TA(timing advance) or RTT (round trip time) parameters. In this case, foreach value of TA or RTT the distribution of distances to the antenna ismeasured in advance in the field. These distributions are used toimprove the calculation of antenna probability at each sub-area.

In an embodiment, for enclosed spaces, e.g. a tunnel, a building ordifferent floors in shops or railway stations, the antenna probabilitiesare determined from maps outlining the enclosed spaces, and for each ofthe enclosed spaces the antenna probability of the antenna serving therespective enclosed space is set to a value which is provided on the mapor to 100%. Thus, it is possible to determine efficiently, if a user islocated in an enclosed space.

In yet another embodiment, the location probabilities are refined usingcumulated historical location probabilities, each of the historicallocation probabilities considering distances traveled by the user.Specifically, the areas can be reduced even more in size using asequence of older location determinations, for example three locationdeterminations every three minutes, taking into account the fact thatusers can only travel with a given maximum speed from older positions tothe current position. This does allow combining several locationprobabilities to a combined location probability which covers a muchsmaller area than the result from one location determination. Thecalculation can be performed online, combining online locationprobabilities pre-calculated for each antenna.

In addition to a computer system and a computer-implemented method forlocating a mobile communication terminal associated with a mobile radionetwork covering a geographical area, the present invention also relatesto a computer program product including computer program code means forcontrolling one or more processors of a computer system, particularly, acomputer program product including a computer readable medium containingtherein the computer program code means.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be explained in more detail, by way ofexample, with reference to the drawings in which:

FIG. 1 shows a block diagram illustrating schematically an exemplaryconfiguration of a system for locating a mobile communication terminalassociated with a mobile radio network.

FIG. 2 shows a flow diagram illustrating an example of a sequence ofsteps executed for locating the mobile communication terminal in ageographical area.

FIG. 3 shows a block diagram illustrating schematically sub-areas of apartial region of a geographical area covered by antennas of the mobileradio network.

FIG. 4 shows a graph illustrating exemplary distributions of the fieldstrengths expected in a sub-area from two different antennas.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

In FIG. 1, reference numeral 1 refers to a mobile communication terminalsuch as a mobile radio (cellular) telephone, a PDA or another portablecomputer. The mobile communication terminal 1 comprises a communicationmodule for communicating (voice and/or data) via mobile radio network 2,e.g. a GSM or UMTS network or another cellular radio network. Asillustrated schematically in FIG. 3, the cellular network comprises aplurality of antennas A1, A2, A3, A4, each covering a more or lessoverlapping area C1, C2, C3, C4 of the geographical area 4. Each antennaA1, A2, A3, A4 is controlled by a base station connected to a mobileswitching center (e.g. MSC) of the mobile radio network 2. The antennasA1, A2, A3, A4 are identified by their identification id in the network,which correspond to the areas C1, C2, C3, C4.

In FIG. 1, reference numeral 3 refers to a computer system connected tothe mobile radio network 2. Computer system 3 includes one or morecomputers, for example personal computers or servers, comprising one ormore processors. Computer system 3 further comprises at least one dataentry and display terminal 38 connected to at least one of itscomputers. Furthermore, computer system 3 comprises a data store 30,e.g. a database and/or one or more data files and various functionalmodules namely a sub-area definition module 31, a field strengthprediction module 32, an antenna probability calculation module 33, anantenna determination module 34, a location probability calculationmodule 35, and a location determination module 36. Preferably, thefunctional modules and the data store 30 are implemented as programmedsoftware modules. The computer program code of the software modules isstored in a computer program product, i.e. in a computer readablemedium, either in memory integrated in a computer of computer system 3or on a data carrier which can be inserted into a computer of computersystem 3. The computer program code of the software modules controls thecomputer(s) of computer system 3 so that the computer system 3 executesvarious functions described in the following paragraphs with referenceto FIGS. 2 to 4.

As illustrated schematically in FIG. 2, computer system 3 is configuredto perform preparatory step S1 for generating, for all sub-areas 41, 43,antenna probabilities which indicate for each sub-area the probability amobile communication terminal 1 located in this sub-area uses therespective antenna A1, A2, A3, A4 for registering and/or communicatingwith the mobile radio network 2. Preparatory step S1 is performedperiodically, e.g. monthly, and/or whenever there is a significantchange in the radio network, e.g. if an antenna A1, A2, A3, A4 is turnedoff, a new antenna is added or settings of an antenna are altered.

Furthermore, computer system 3 is configured to perform step S2 forlocating the mobile communication terminal 1 in the geographical area 4.Step S2 is performed as requested by a user of data entry terminal 3, acontrol application running on computer system 3, or a location basedservice application running on computer system 3 or a remote computersystem.

In step S11, sub-area definition module 31 divides the geographical area4 into a plurality of sub-areas 41, 43, as illustrated schematically inFIG. 3. In the example of FIG. 3, the geographical area 4 is dividedinto a grid 40 of equal-sized squares, each square defining a sub-area41, 43. For example, the sub-areas 41, 43 are squares of 100 m×100 m.One skilled in the art will understand that alternative shapes ofsub-areas are possible, for example, the geographical area 4 may bedivided into hexagons arranged in a comb structure. Furthermore, it isalso possible to have various sizes of sub-areas, for example smallersub-areas may be used in zones of increased interest and/or population.Typically, a sub-area is defined by a unique identifier and one or moreparameters which describe direct or indirect the position coordinates.Depending on the embodiment, a sub-area is further defined by sub-areatype, size and/or shape information. Thus, sub-area definition module 31defines and stores in the data store 30 a list or array comprising thedefined sub-areas 41, 43 of the geographical area 4. In an embodiment,the sub-area definition module 31 is configured to read the definitionof the sub-areas from a data file.

In an embodiment, the sub-area definition module 31 is configured tosupport manual or file based entry of the antenna probability ofantennas, which would require in the following steps a full 3D modelingof radio propagation, taking into account the exact position of theantenna inside of a 3D physical environment, as for example an enclosedspace such as in a tunnel, or on different floors in shops or railwaystations. As there are not many of these enclosed antennas and thepropagation of the radiation does usually follow the physical shape ofthe environment where they are installed, the antenna probability of theenclosed antennas are manually acquired based on maps where theseantennas are located and loaded into the data store 30. In an embodimentshapes assigned to enclosed antennas are loaded into the data store 30and all antenna probabilities are set to 100% when the sub-area isinside an enclosed space including an enclosed antenna.

In step S12, field strength prediction module 32 calculates, for all thesub-areas 41, 43 defined for the geographical area 4, the fieldstrengths expected in the respective sub-area 41, 43 from the antennasA1, A2, A3, A4 of the mobile radio network 2, considering data abouttopography and power characteristics associated with the antennas A1,A2, A3, A4. Field strength prediction modules 32 are availablecommercially, e.g. offered by Aricom International. Preferably, only theantennas A1, A2, A3, A4 having the highest expected field strengthvalues are stored for a sub-area 41, 43 in data store 30. For example,the field strength values are stored for a defined (configurable) numberof the strongest antennas A1, A2, A3, A4, e.g. for the seven or fourteenstrongest antennas. Table 1 shows exemplary entries of expected fieldstrengths in data store 30. In the example of Table 1, a field strengthof −41 dBm is expected in sub-area 41 for antenna A4, whereas a fieldstrength of −52 dBm is expected in the same sub-area for antenna A1;likewise, in sub-area 43, a field strength of −42 dBm is expected forantenna A3, whereas a field strength of −48 dBm is expected for antennaA4. In addition or as an alternative to a unique identifier, antennadata may include antenna coordinates or grid positions, for example.Moreover, in addition to the field strength value, further fieldstrength data may include standard deviations for the expected fieldstrength distribution of the antenna in the respective sub-area. Thus,the field strength for a given sub-area i is preferably modeled as arandom variable having a normal distribution with expected value d_(i)and standard deviation s_(i). Modeling the field strength as adistribution is necessary because the real field strengths do have bigvariations, depending on the exact position inside the sub-area,location of buildings, weather conditions, how the mobile communicationterminal is oriented in space and many other factors. Instead ofconsidering all these factors into the model calculation, the resultingnormal distribution can be used and its standard deviation measured infield tests where the real field strengths are compared with expectedfield strengths for many test calls.

TABLE 1 expected field strength sub-area antenna field further fieldsub-area sub-area antenna antenna strength strength identifier dataidentifier data value data . . . . . . . . . . . . . . . . . . 41 . . .A4 . . . −41 dBm . . . 41 . . . A1 . . . −52 dBm . . . 41 . . . A3 . . .−55 dBm . . . . . . . . . . . . . . . . . . . . . 43 . . . A3 . . . −42dBm . . . 43 . . . A4 . . . −48 dBm . . . 43 . . . A2 . . . −51 dBm . .. . . . . . . . . . . . . . . . . . .

In step S13, antenna probability calculation module 33 determines foreach sub-area 41, 43 the antenna probabilities for the antennas A1, A2,A3, A4.

In sub-step S131, based on the expected field strength values stored inthe database or collection of files 30, antenna probability calculationmodule 33 calculates for each sub-area 41, 43 the antenna probabilities,i.e. the probability in the respective sub-area 41, 43, the antenna A1,A2, A3, A4 is being used by a mobile communication terminal 1 forregistering and/or communicating with mobile radio network 2, asoutlined below.

In FIG. 4, x₁ refers to the expected field strength (here −41 dBm) of anantenna A1 at a given location, i.e. in a given sub-area 41, 43.Reference numeral D₁ refers to the distribution of the real fieldstrength which can be measured at this sub-area with a mobilecommunication terminal. In this sample it is likely that the real fieldstrength will be around −41 dBm, but sometimes the field strength is −45dBm, sometimes −37 dBm, it will change depending on the precise locationwithin the sub-area 41, 43, e.g. within the 100 m×100 m square, theweather, the type of terminal, how the terminal is oriented in space,etc. Likewise, x₂ refers to the expected field strength (here −55 dBm)of another antenna A2 in the same sub-area 41, 43, and reference numeralD₂ refers to the distribution of the real field strength of antenna A2.For calculating the probability that the mobile communication terminal 1will use antenna A1 in the respective sub-area 41, 43, distribution D₁of the real field strength of antenna A1 is divided into small sectors,such as sector S showing the probability that the real field strength ofantenna A1 is in a small range between −40 dBm and −41 dBm. Forcalculating the probability the real field strength of antenna A1 isbetween −40 dBm and −41 dBm, and higher than the real field strength ofantenna A2 (resulting in the use of antenna A1), the following twoprobabilities are used:

-   -   1) Probability that the real field strength of antenna A1 is        between −40 dBm and −41 dBm, which corresponds to the area of        section S between −40 dBm and −41 dBm; and    -   2) Probability that the real field strength of antenna A2 will        be less than −41 dBm, which corresponds to area F below −41 dBm.

As probabilities 1) and 2) are independent, the probability that bothconditions are met at the same time can be calculated by multiplying theprobabilities 1) and 2) (product of areas S and F).

The above calculated probability is restricted to the case where antennaA1 is between −40 dBm and −41 dBm. For calculating the probability 3)for all real fields strengths of antenna A1, the limit is calculated forall summed products of S and F for all real field strengths between −infinity to + infinity, while letting the width of the sector S go tozero. This results in the following integral:

p_(A 1) = ∫_(−∞)^(∞)N(x, d_(A 1), s_(A 1)) ⋅ F(x, d_(A 2), s_(A 2))⋅ x

N(x, d_(A1), S_(A1)) is the normal distribution of the real fieldstrength x of antenna A1, with expected power level d_(A1) and standarddeviation s_(A1):

${N\left( {x,d_{A\; 1},s_{A\; 1}} \right)} = {\frac{1}{s_{A\; 1}\sqrt{2\; \pi}}^{{- \frac{1}{2}}{\{\frac{x - d_{A\; 1}}{s_{A\; 1}}\}}^{2}}}$

F(x, d_(A2), s_(A2)) is the probability the real field strength y of theantenna A2 with expected power level d_(A2) and standard deviations_(A2) is lower than x:

F(x,d _(A2) ,s _(A2))=∫_(−∞) ^(x) N(y,d _(A2) ,s _(A2))dy

For example, F(−60, −40, 5) is the probability the real field strengthwill be between − infinity and −60, for a normal distribution at x=−40and a standard deviation of 5.

Taking into account another antenna A3 is straightforward, as it isanother independent condition which has to be met, so the antenna A1 isstill used rather than the antennas A2 or A3. So the probability 3)outlined above can be extended with this additional condition, which isthe probability that the field strength of antenna A3 is smaller than x.The resulting probability 4) is:

p_(A 1) = ∫_(−∞)^(∞)N(x, d_(A 1), s_(A 1)) ⋅ F(x, d_(A 2), s_(A 2)) ⋅ F(x, d_(A 3), s_(A 3))⋅ x

More antennas are taken into account the same way as antennas A2 and A3.In addition the variable substitution d_(A1)< >d_(Ai) and s_(A1)<>d_(Ai) does allow to calculate the probability the call will go to oneof the other antennas A_(i). This does allow rephrasing the calculation4) in a general way. So the antenna probability p_(Ai) 5) that themobile communication terminal will connect to a given antenna A_(i) withan expected power level d_(Ai) and standard deviation s_(Ai) is givenby:

$p_{Ai} = {\int_{- \infty}^{\infty}{{N\left( {x,d_{Ai},s_{Ai}} \right)} \cdot {\prod\limits_{{j = 1},{j \neq i}}^{n}\; {{F\left( {x,d_{Aj},s_{Aj}} \right)} \cdot \ {x}}}}}$

In an embodiment, for each network type the same standard deviation isused for s_(Ai). For GMS networks, a deviation of 10 is used, for UMTSnetworks a deviation of 4. In a further embodiment, higher deviationsare used with increased distance of a sub-area 41, 43 from therespective antenna A1, A2, A3, A4. For example, a standard deviation ofapproximately 8 is used for UMTS networks, if the antenna is locatedfarther than 5 km from the respective sub-area.

As the mobile communication terminals 1 cannot make a call-setup, if thefield strength is below a certain value, the lower limit in the formulasoutlined above is adjusted from − infinity to a defined (configurable)minimum field strength, depending on the network type of the cell beingGSM or UMTS, for example. Furthermore, as the mobile communicationterminal 1 and the mobile radio network 2 do not distinguish in theantenna selection field strength values higher than a defined(configurable) value, e.g. −40 dBm, all expected field strength valuesabove this value are limited to this value.

The integral cannot be solved algebraically. As the input data isimprecise, it is not necessary to have an infinite precision in theprobability calculation. So N(x, d_(i), s_(i)) can be approximated by 0in the regions of x≦d_(i)−5s_(i) and x≧d_(i)+5s_(i)]. Which is the sameas when the boundaries]−∞,∞[are replaced by [d_(i)−5s_(i),d_(i)+5s_(i)]. In a next approximation step the interval is divided intoa finite number of segments, e.g. 10 or 20, for numerical integrationwith the Simpson's method. For speeding up the automatic computation,values of N(x_(k), 0, 1) and F(y_(k), 0, 1) can be precomputed andstored for different values of x_(k) or y_(k), respectively.

In step S132, antenna probability calculation module 33 sets the antennaprobabilities of enclosed antennas to the values loaded in step S11 intodata store 30. In an embodiment all antenna probabilities are set to100%, which are inside enclosed spaces assigned to enclosed antennas,which were loaded before in step S11 into data store 30.

In step S133, antenna probability calculation module 33 takes intoaccount mobile communication terminals, configured to switchautomatically between different networks as for example GSM or UMTS.This does affect the location area. The implementation of antennaprobability calculation module 33 depends on how multiband mobilecommunication terminals select the network type. This has to beestimated in the field or in a lab using multiband terminals withdifferent signal levels from multiple networks. In an embodiment ofantenna probability calculation module 33, for GSM and UMTS, the antennaprobabilities are calculated separate for each network, as according tothe measurements multiband mobile communication terminals always preferUMTS whenever available. This way no terminal detection is necessary. Itdoes only have the disadvantage that GSM areas could be smaller formultiband mobile communication terminals in GSM areas, where there isUMTS coverage as long as UMTS is not turned off on the mobilecommunication terminal. In an embodiment, it is possible to use a mobilecommunication terminal detection and calculate the GSM areas formultiband mobile communication terminals separately; setting on eachsub-area the antenna probability of all GSM antennas to zero if there isan UMTS antenna available with more than a defined (configurable)minimum field strength.

The antenna probabilities resulting from step S13 are stored temporarilyfor each antenna in the memory of the computer system 3 or in data store30. For example, the antenna probabilities are stored for a defined(configurable) number of the strongest antennas A1, A2, A3, A4, e.g. forthe seven or fourteen strongest antennas. Table 2 shows exemplaryentries of calculated antenna probabilities in data store 30. In theexample of Table 2, for sub-area 41, it is expected that with aprobability of 50% antenna A4 will be used, whereas the probability ofantenna A1 is 25%; likewise, for sub-area 43, a probability of 40% isexpected for antenna A3, whereas a probability of 35% is expected forantenna A4. One skilled in the art will understand that Tables 1 and 2may be combined in one or more files or in a common table.

TABLE 2 sub-area antenna sub-area sub-area antenna antenna antennaidentifier data identifier data probability . . . . . . . . . . . . . .. 41 . . . A4 . . . 50% 41 . . . A1 . . . 25% 41 . . . A3 . . . 15% . .. . . . . . . . . . . . . 43 . . . A3 . . . 40% 43 . . . A4 . . . 35% 43. . . A2 . . . 10% . . . . . . . . . . . . . . .

In step S21, antenna determination module 34 determines for a particularmobile communication terminal 1 the antenna A1, A2, A3, A4 used, i.e.the antenna currently or last used, from identification data provided bythe mobile radio network 2, e.g. cell identifier or base stationidentifier. In different embodiments and/or applications, thisinformation is obtained by antenna determination module 34 from the MSCof the mobile radio network 2, the Home Location Register (HLR)associated with the mobile communication terminal 1, or the VisitorLocation Register (VLR) or another network component of the mobile radionetwork 2. In a further embodiment, antenna determination module 34 isconfigured to send a message to the mobile communication terminal 1,e.g. an (invisible) SMS (Short Messaging Services) or USSD (UnstructuredSupplementary Service Data) message, to trigger the mobile communicationterminal 1 to use an antenna A1, A2, A3, A4 from the current locationand, thus, update the respective identification information in themobile radio network 2. In a further embodiment, the antennadetermination module 34 is configured to receive identificationinformation for defining the antenna used by the user or the mobilecommunication terminal 1, respectively, from an operator or a softwareapplication, for example.

In step S22, location probability calculation module 35 calculates foreach sub-area of an antenna a location probability, which is theprobability that the user is in the respective sub-area.

In an embodiment location probability calculation module 35 firstreduces the size of the user location areas using additional parametersfrom the network, obtained by antenna determination module 34, forexample TA (timing advance) or RTT (round trip time). These parameterscan be used to indicate the probability the sub-area does have therespective parameter, depending on the distance between the sub-area andantenna. Field tests are made in advance to estimate the distribution ofdistance for each possible value of one of these parameters. If,depending on the network 2, antenna determination module 34 is able todeliver such a parameter, for example for a call timing advance of four(4), it is possible to calculate the probability that both will happen:the mobile communication terminal 1 selects at a sub-area a givenantenna AND the network parameter from antenna determination module 34is four (4). As both conditions are independent the combined probabilitycan be calculated multiplying the antenna probability and theprobability for the parameter from antenna determination module 34 beingfour (4). The resulting combined probability is used in the followingsteps as an improvement for the antenna probability calculated before.

The sum of all location probabilities of an antenna is one (1), as it isknown from the network which antenna is used. This allows calculatingthe distribution of location probability P_(u) in all sub-areas from theantenna probability P_(Ai) calculated in the steps before and the totalantenna probability of all n sub-areas:

${P_{Li} = \frac{P_{Ai}}{\sum\limits_{n}P_{Aj}}},$

The calculated location probabilities are calculated and stored for eachantenna and its sub-areas 41, 43 in data store 30. It must be noted thatone antenna can have one or more sub-areas 41, 43 with a locationprobability >0, and one sub-area 41, 43 can have more than one antennawith a location probability >0.

In an embodiment, location probability calculation module 35 reduces thesize of areas with a minimal antenna probability using a sequence ofhistorical location determinations, calculating for each locationdetermination the location probability as in the steps before,calculating for each location determination the time until the lastlocation determination, calculating for each location determination themaximum distance the user can have traveled in all directions andspreading for each location determination all probabilities of therespective sub-area in the range between zero and the max distance. Theresulting location probabilities for each location determination arethen blended multiplying the resulting location probabilities. Theresulting combined location probabilities are used in the followingsteps as an improvement for the location probabilities calculatedbefore.

In step S23, location determination module 36 optimizes the locationprobabilities, correcting in this last step errors which are caused bylimitations of the granularity of the grid or input data used forcalculating the field strength predictions. In one embodiment, tocorrect for errors caused by the limitation of the granularity of thegrid or comb structure, for each antenna all location probabilities >0are expanded at the border twice the size of the grid, e.g. 200 meters.In another embodiment, the location determination module 36 is furtherconfigured to show the resulting location probabilities for each antennaA1, A2, A3, A4 graphically on a display of data entry terminal 38, thesub-areas 41, 43 having a location probability >0, for example colorcoded in a way a high value of the location probability correlate withcolor schemas as for example black/grey/white or different shades of oneor more colors like, for example, white, blue and red. In yet anotherembodiment, e.g. in order to adhere to government regulations, generatedand displayed is a location area, based on the determined locationprobabilities, for example an elliptical location area, representativeof the geographical area where the mobile communication terminal 1 isexpected to be located when the respective antenna was used by themobile communication terminal 1. In a further embodiment, computersystem 3 comprises a communication module configured to transmit thedetermined location probabilities, a graphic representation of thelocation probabilities and/or the (elliptical) location area to a mobilecommunication terminal 1. In this further embodiment, the mobilecommunication terminal 1 is configured to show the received locationprobabilities and/or location area on a map, e.g. using geographicalinformation services such as Google Maps by Google Inc.

1-16. (canceled)
 17. A method, comprising: determining signal sourceprobabilities for a plurality of sub-areas of a geographic area coveredby a plurality of signal sources, wherein, for each one of the pluralityof sub-areas: the signal source probabilities are determined based onprobable field strengths of the plurality of signal sources for the oneof the plurality of sub-areas; and the signal source probabilitiesindicate the probability that a mobile device, located in the one of theplurality of sub-areas, is operable to detect a particular signal sourcefor communicating.
 18. The method of claim 17, wherein determining thesignal source probabilities comprises calculating expected fieldstrengths in the plurality of sub-areas.
 19. The method of claim 17,wherein determining the signal source probabilities comprises obtainingpower information indicating a detected power of respective signalsreceived by the mobile device from multiple transmitters.
 20. The methodof claim 17, wherein the sub-areas of the geographic area comprise aplurality of sample positions, each sample position being a possiblelocation of the mobile device.
 21. The method of claim 17, comprisingdetermining known locations of the signal sources using at least thesignal source probabilities.
 22. The method of claim 17, comprisingdetermining a probability model based on the signal sourceprobabilities.
 23. The method of claim 22, wherein the probability modelis a three dimensional model.
 24. The method of claim 17, comprisingdetermining each signal source probability based at least in part onpower of a first signal and at least in part on power of a second signalas measured in the sub-area, wherein the first signal originates from afirst transmitter and the second signal originates from a secondtransmitter.
 25. The method of claim 17, wherein the plurality ofsub-areas form a geographic grid.
 26. The method of claim 25, whereinthe geographic grid is a three-dimensional space having a length, awidth, and a height.
 27. A system, comprising: one or more computers;and a non-transitory storage device storing instructions operable tocause the one or more computers to perform operations comprising:determining signal source probabilities for a plurality of sub-areas ofa geographic area covered by a plurality of signal sources, wherein, foreach one of the plurality of sub-areas: the signal source probabilitiesare determined based on probable field strengths of the plurality ofsignal sources for the one of the plurality of sub-areas; and the signalsource probabilities indicate the probability that a mobile device,located in the one of the plurality of sub-areas, is operable to detecta particular signal source for communicating.
 28. The system of claim27, wherein determining the signal source probabilities comprisescalculating expected field strengths in the plurality of sub-areas. 29.The system of claim 27, wherein determining the signal sourceprobabilities comprises obtaining power information indicating adetected power of respective signals received by the mobile device frommultiple transmitters.
 30. The system of claim 27, wherein the sub-areasof the geographic area comprise a plurality of sample positions, eachsample position being a possible location of the mobile device.
 31. Thesystem of claim 27, wherein the operations comprise determining knownlocations of the signal sources using at least the signal sourceprobabilities.
 32. The system of claim 27, wherein the operationscomprise determining a probability model based on the signal sourceprobabilities.
 33. The system of claim 32, wherein the probability modelis a three dimensional model.
 34. The system of claim 27, wherein eachsignal source probability is determined based at least in part on powerof a first signal and at least in part on power of a second signal asmeasured in the sub-area, the first signal originates from a firsttransmitter and the second signal originates from a second transmitter.35. The system of claim 27, wherein the plurality of sub-areas form ageographic grid.
 36. The system of claim 35, wherein the geographic gridis a three-dimensional space having a length, a width, and a height.